Image “stitching,” that is, joining multiple images edge-to-edge to create a single combined image, has been gaining prominence in many application areas including, for example, computer vision, digital maps, satellite imaging, medical imaging, and even amateur photography. For example, to create an immersive virtual-reality experience, multiple cameras may be used to capture source images covering different parts of a scene. These source images are then stitched together, to form a 360-degree panorama that can be used in applications such as interactive panoramic movies, architectural walk-through, multi-node movies, and other applications that generate a virtual 3D environment using images acquired from the real world.
Because the source images used for panorama stitching may be generated by different imaging devices, at different times, and/or under different illumination conditions, a well-known challenge for panorama stitching is maintaining consistency in image parameters of the source images, which may exhibit differences in brightness and/or color. To solve the inconsistency issue, conventional methods adjust adjacent source images to ensure that luminance and/or chrominance histograms (indicating variations in brightness) in the overlapping regions are matched. Such adjustments can cause undesirable side effects in certain images. That is, certain images can have over-exposure or under-exposure after the adjustments.
For example, when a first image appears darker than other images, the first image must be adjusted to increase its brightness. An adjustment factor is determined for the image to be adjusted. The brightness of the image is adjusted based on the adjustment factor. In other words, the luminance value of every pixel is adjusted based on the adjustment factor. However, since the distribution of the brightness of the pixels is typically not uniform in the image, the image typically includes some areas that are darker than other areas. If the darker areas and the brighter areas of the image are both adjusted using the same adjustment factor, the brighter areas may appear over-exposed after the adjustment. Alternatively, if the first image appears brighter than other images, its brightness should be reduced. If a single adjustment factor is used to adjust the brightness of both the darker areas and brighter areas of the image, the darker areas may appear under-exposed after the adjustment. Due to these side effects, the overall quality of the stitched panorama image may be reduced. Therefore, a method that can prevent or reduce over exposure or under exposure during brightness adjustment is needed.
The disclosed systems and methods address one or more of the problems listed above.